Awesome GitHub RepositoriesAlgorithm Implementations

Baselines is a comprehensive suite of frameworks for reinforcement learning algorithm implementation, imitation learning, and training orchestration. It provides a library of standardized learning algorithms used to benchmark and replicate research results, alongside a deep learning policy framework for constructing neural network architectures such as multi-layer perceptrons, convolutional networks, and long short-term memory networks. The project includes a specialized imitation learning toolkit that enables agents to mimic expert behavior through behavior cloning and generative adversarial

MLAlgorithms is an educational machine learning algorithm library consisting of core predictive models implemented from scratch in Python. It serves as a reference for developers to study the internal logic and mathematical workings of these models through clean, minimal implementations. The codebase focuses on the study of algorithm implementation and machine learning education, providing a way to understand internal mechanics by building components without relying on heavy external libraries. The project utilizes object-oriented encapsulation and NumPy-based vectorization to manage model s

Minimal and Clean Reinforcement Learning Examples

Modularized Implementation of Deep RL Algorithms in PyTorch

ChainerRL is a deep reinforcement learning library built on top of Chainer.

A deep Q learning demonstration using Google Tensorflow

🕹️ A diverse suite of scalable reinforcement learning environments in JAX

Deep Reinforcement Learning library for humans

Persistent advantage learning dueling double DQN for the Arcade Learning Environment

Code for the Black-DROPS algorithm: "Black-Box Data-efficient Policy Search for Robotics", IROS 2017/ICRA 2018